Clinical Trial

Pre-Symptomatic Detection of Impending Decompensation in Heart Failure Through Voice Data

Study acronym: PRE-DETECT-HF
Active, Not Recruiting
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Record status
This record was last updated March 2, 2026 (before its estimated June 2026 completion). Its status may not reflect the trial's current state.
Summary
PRE-DETECT-HF is a prospective, single-arm observational study evaluating a voice-based machine learning algorithm for early detection of heart failure decompensation. 123 patients hospitalized for acute decompensated or de-novo heart failure will be enrolled across three sites in the Netherlands and Spain. Patients make daily voice recordings via a smartphone app and answer symptom questions for 6 months. The algorithm analyzes voice patterns compared to a baseline recording at discharge. Treatment decisions are based on symptom data only; voice-based predictions are analyzed retrospectively after study completion. The primary endpoint is sensitivity of the voice-based software in detecting heart failure deterioration, defined as heart failure hospitalization, or intensification of heart failure therapy. Secondary endpoints include app adherence, usability, and associations between voice data and blood biomarkers.
Trial Details
NCT Number NCT07443969
Lead Sponsor Noah Labs
Collaborators: Hospital Clinic of Barcelona, Maastricht University, Zuyderland Medical Centre
Conditions Heart Failure, Chronic Heart Failure, Chronic Heart Disease
Enrollment 123 participants
Start Date 2025-01-09
Primary Completion 2026-06 (estimated)
Study Completion 2026-06 (estimated)
Updated on ClinicalTrials.gov 2026-03-02